{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 目录\n",
    "1. 打印 Hello World\n",
    "2. 变量\n",
    "3. 标准数据类型\n",
    "4. type()和类型转换\n",
    "5. 运算符\n",
    "6. 字符串格式化、索引、切片\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hello World'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"Hello World\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello World\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello World\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello World\n"
     ]
    }
   ],
   "source": [
    "i = \"Hello World\"\n",
    "print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'World'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i = \"World\"\n",
    "i"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 标准数据类型\n",
    "- 数字类型\n",
    "  - int\n",
    "  - float\n",
    "  - bool\n",
    "  - complex\n",
    "- 集合类型\n",
    "  - list\n",
    "  - set\n",
    "  - tuple\n",
    "  - dict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 整数\n",
    "* INT32\n",
    "* INT16\n",
    "* INT8\n",
    "* INT4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i = 1\n",
    "i"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 浮点数\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "* FP64\n",
    "* FP32\n",
    "* FP16\n",
    "* BF16\n",
    "* FP8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.2"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i = 3.2\n",
    "i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3100000.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3100000\n",
    "3.1E+6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.00031"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 0.00031\n",
    "3.1e-4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 字符串\n",
    "- 字符串\n",
    "- 字符串格式化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hello World'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"World\"\n",
    "\n",
    "f\"Hello {s}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"中华人民共和国\"\n",
    "len(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'中华人民共和国world'"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s + \"world\"\n",
    "f\"{s}world\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'和'"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s[-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'华民'"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s[1:5:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'中华人民共'"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'国和共民人华中'"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'中华人民 共和国'"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"  中华人民 共和国  \"\n",
    "s.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(True, False)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"中华人民共和国\"\n",
    "s.startswith(\"中华\"),s.endswith(\"共和国1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"中华人民共和国人民\"\n",
    "#s.index(\"人民1\")\n",
    "s.find(\"人民1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'HELLO WORLD'"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"hello world\"\n",
    "#s.capitalize()\n",
    "#s.upper()\n",
    "s.lower()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 类型转换\n",
    "- type()\n",
    "- int()\n",
    "- float()\n",
    "- str()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "int(3.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "float(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'3.2'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(3.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.2"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "float(\"3.2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 运算符\n",
    "\n",
    "- 算术运算符：+、-、*、/、%、//、**\n",
    "\n",
    "- 比较运算符：==、!=、>、>=、<、<=\n",
    "\n",
    "- 赋值运算符：=、+=、-=、\n",
    "\n",
    "- 逻辑运算符：and、or、not\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 10)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i=1004\n",
    "i%100,i//100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(256, 1.4142135623730951)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2**8,2**0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(False, True)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "100 == 1000,100!=1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i = 1\n",
    "# i = i + 1\n",
    "i += 1\n",
    "i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(True, False)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i=100\n",
    "i > 10 and i < 1000, not i==100"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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